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Record W3095334969 · doi:10.1111/jocn.15545

Designing paper‐based records to improve the quality of nursing documentation in hospitals: A scoping review

2020· review· en· W3095334969 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Nursing · 2020
Typereview
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsCentre for Global Health ResearchHospital for Sick ChildrenPublic Health OntarioUniversity of Toronto
FundersWellcome Trust
KeywordsDocumentationCINAHLMedical recordMEDLINEMedicineNursingHealth careNursing processNursing careComputer sciencePsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: Inpatient nursing documentation facilitates multi-disciplinary team care and tracking of patient progress. In both high- and low- and middle-income settings, it is largely paper-based and may be used as a template for electronic medical records. However, there is limited evidence on how they have been developed. OBJECTIVE: To synthesise evidence on how paper-based nursing records have been developed and implemented in inpatient settings to support documentation of nursing care. DESIGN: A scoping review guided by the Arksey and O'Malley framework and reported using PRISMA-ScR guidelines. ELIGIBILITY CRITERIA: We included studies that described the process of designing paper-based inpatient records and excluded those focussing on electronic records. Included studies were published in English up to October 2019. SOURCES OF EVIDENCE: PubMed, CINAHL, Web of Science and Cochrane supplemented by free-text searches on Google Scholar and snowballing the reference sections of included papers. RESULTS: 12 studies met the eligibility criteria. We extracted data on study characteristics, the development process and outcomes related to documentation of inpatient care. Studies reviewed followed a process of problem identification, literature review, chart (re)design, piloting, implementation and evaluation but varied in their execution of each step. All studies except one reported a positive change in inpatient documentation or the adoption of charts amid various challenges. CONCLUSIONS: The approaches used seemed to work for each of the studies but could be strengthened by following a systematic process. Human-centred Design provides a clear process that prioritises the healthcare professional's needs and their context to deliver a usable product. Problems with the chart could be addressed during the design phase rather than during implementation, thereby promoting chart ownership and uptake since users are involved throughout the design. This will translate to better documentation of inpatient care thus facilitating better patient tracking, improved team communication and better patient outcomes. RELEVANCE TO CLINICAL PRACTICE: Paper-based charts should be designed in a systematic and clear process that considers patient's and healthcare professional's needs contributing to improved uptake of charts and therefore better documentation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.155
GPT teacher head0.563
Teacher spread0.408 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it